Keesup Choe of PredictX suggests that targeted selling algorithms using artificial intelligence can help buyers control spend and create leverage for supplier negotiations.
As modern-age consumers, we have more or less accepted we are being monitored through our devices, search history, online shopping activity and use of social media. We know there are algorithms in play, yet it is often only those seeking profit who attempt to master their complexities. Search engine optimization, paid search and social advertising are examples of companies using this technology to increase their bottom lines.
These targeted selling algorithms permeate corporate travel. Hotels use revenue management data intelligence software to sell the most room nights at the highest prices, and determine channel mix.
The 14-day advance purchase rule we use to get cheaper airfares becomes less useful as airlines apply more advanced revenue management algorithms and tactical fares to fill seats.
What if buyers applied the same technological innovation suppliers use to control spend instead? What if the algorithms pulling data on what travelers booked and what was available were just as sophisticated and immediate as those used by Google and Facebook to monitor our personal preferences for targeted advertising?
Personalization in booking tools aims to provide options to travelers based on their info and booking patterns, and travel policy — much like how algorithms in online shopping sites like Amazon work.
As much as travel managers may want to adopt these algorithms, what influence would they have in controlling them? Like most content aggregators, online booking tools do not solely market their services to buyers. They exist, in essence, as a marketplace where many businesses and their competing priorities operate within.
Buyers need to start putting themselves in the driver’s seat when it comes to creating and investing in technology to benefit their own bottom lines rather than those of their suppliers.
How do we achieve this? How do buyers use technology to tell travelers which room to choose, and at what price? Sure, OBTs marry travel policy with supplier and aggregator commercial goals, but there may be a better way.
Travel managers look at spend analytics to choose which suppliers to negotiate deals with and whom to classify as “preferred.” But if we go one step further, we can use targeted selling/machine learning to measure ongoing spend data and prioritize travel offers in a booking system.
Just as Facebook uses personal data and then pushes recommended content and ads, we can use travel program spend data to push specific hotel rooms, airfares and other travel offers to the top of each traveler’s booking options. Imagine a system that automatically knows which supplier needs higher demand and pushes the associated offer to the top of travelers’ lists.
That could result from suppliers targeting specific time periods, routes, locations, etc., where they need greater volumes. Or it could stem from companies more actively trying to meet contract goals. For example, if a company’s airline contract requires a certain number of bookings on a certain route, real-time and intelligent spend analytics can determine if the client is falling short and prioritize that airline in search results.
It’s possible to go a step further and introduce rate shopping into the mix rather than relying on only the travelers’ preferences, TMC priorities and a static travel policy. No doubt better deals will be booked.
This has the potential to save a lot of time for travel managers. They currently analyze the value of each supplier at regular intervals during the year and make appropriate supplier management and policy changes. This process can be cut out altogether, instead using artificial intelligence to continuously monitor spend and change the way travelers book.
No doubt the technology will be challenging to build, but if you want to develop the processes to influence the way travelers book, now is the time to do it. When it comes to the current business travel industry, disruption is most certainly in the air.
Targeted selling algorithms are not just for using our data to make suppliers more money. We all stand a chance to gain. The only parties who will lose are those who do not create and invest in the algorithms that will shape our future travel buying ecosystem.